@article {70379, title = {Whole-body 3D kinematics of freely behaving Drosophila}, journal = {bioRxiv}, year = {2026}, month = {2026 May 04}, abstract = {

Understanding how nervous systems generate coordinated movement requires precise measurement of body kinematics during natural behavior. The fruit fly, Drosophila, is a model organism with sophisticated behavior and well-studied neural circuits, but tracking fly movements in 3D remains challenging because of their teeny bodies, rapid movements, and frequent self-occlusions. Here we present a pipeline for markerless, full-body 3D pose estimation of fly terrestrial behavior, combining seven synchronized high-speed cameras to capture whole-body kinematics at 800 frames per second. We trained a hybrid 2D/3D deep learning model to track 50 keypoints, then refined them to produce anatomically feasible kinematic trajectories through a retargeting process that solved an inverse kinematics problem constrained by a biomechanical body model. Analysis of 3D kinematics revealed that flies perform grounded running across their full speed range, without transitioning between discrete gaits. Using multi-animal tracking, we found that courting males coordinate both wings during song and modulate body pitch to track the female{\textquoteright}s vertical position. Our open-source pipeline and 3D kinematic dataset of fly behavior provide a foundation for neuromechanical modeling and mechanistic studies of motor control in a genetically tractable model organism.

}, doi = {10.64898/2026.05.03.722293}, url = {https://www.biorxiv.org/content/early/2026/05/04/2026.05.03.722293}, author = {Ispizua, Juan I. and Abe, Elliott T. T. and Yan, Jinyao and Othayoth, Ratan and Sawtelle, Steven and Atkins, Felisha and Shiozaki, Hiroshi and Meier, Niko R. and Wong, Jovanka and Tran, Tiffany T. and Mori, Catherine K. and Voigts, Jakob and Stern, David L. and Brunton, Bingni W. and Tuthill, John C. and Johnson, Robert Evan} } @article {47422, title = {The collection of MicroED data for macromolecular crystallography.}, journal = {Nature Protocols}, volume = {11}, year = {2016}, month = {2016 May}, pages = {895-904}, abstract = {

The formation of large, well-ordered crystals for crystallographic experiments remains a crucial bottleneck to the structural understanding of many important biological systems. To help alleviate this problem in crystallography, we have developed the MicroED method for the collection of electron diffraction data from 3D microcrystals and nanocrystals of radiation-sensitive biological material. In this approach, liquid solutions containing protein microcrystals are deposited on carbon-coated electron microscopy grids and are vitrified by plunging them into liquid ethane. MicroED data are collected for each selected crystal using cryo-electron microscopy, in which the crystal is diffracted using very few electrons as the stage is continuously rotated. This protocol gives advice on how to identify microcrystals by light microscopy or by negative-stain electron microscopy in samples obtained from standard protein crystallization experiments. The protocol also includes information about custom-designed equipment for controlling crystal rotation and software for recording experimental parameters in diffraction image metadata. Identifying microcrystals, preparing samples and setting up the microscope for diffraction data collection take approximately half an hour for each step. Screening microcrystals for quality diffraction takes roughly an hour, and the collection of a single data set is \~{}10 min in duration. Complete data sets and resulting high-resolution structures can be obtained from a single crystal or by merging data from multiple crystals.

}, issn = {1750-2799}, doi = {10.1038/nprot.2016.046}, author = {Shi, Dan and Nannenga, Brent L and de la Cruz, M Jason and Liu, Jinyang and Sawtelle, Steven and Calero, Guillermo and Reyes, Francis E and Hattne, Johan and Gonen, Tamir} }